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1. Data Visualization Tool for Covid-19 and Crime Data

   Sean Walker and Sharad Sharma (January 2021, Proceeding of the IEEE International Conference on Computational Science and Computational Intelligence, (CSCI'21),Symposium of Big Data and Data Science (CSCI-ISBD))

   Data visualization gives a visual context through maps or graphs and makes it easier for the human mind to identify trends, patterns, and outliers within large data sets. The understanding of patterns and location of crime through data visualization and data mining techniques approaches is a very useful tool which can help and support police forces. Identification of crime characteristics and types are the first step for developing further analysis. This paper describes the development of data visualization tool using Unity 3D and Maptitude GIS for visualization of Baltimore COVID-19 and crime data. This effort aims to determine parameters that influence the vulnerability of African Americans to COVID-19 during the pandemic. The study has found that the factors shown to be influential in a person’s susceptibility include neighborhood and physical environment, housing, occupation, education, income, and wealth gaps. The data collected from Baltimore incident reports and findings shared by Maryland SOA office shows that crime has increased and decreased in different areas during the time of COVID pandemic. 

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2. Situational awareness of COVID pandemic data using virtual reality

   https://doi.org/10.2352/ISSN.2470-1173.2021.13.ERVR-177  

   Sharma, Sharad; Bodempudi, Sri Teja (March 2021, Electronic Imaging)

   null (Ed.)

   Situational awareness provides the decision making capability to identify, process, and comprehend big data. In our approach, situational awareness is achieved by integrating and analyzing multiple aspects of data using stacked bar graphs and geographic representations of the data. We provide a data visualization tool to represent COVID pandemic data on top of the geographical information. The combination of geospatial and temporal data provides the information needed to conduct situational analysis for the COVID-19 pandemic. By providing interactivity, geographical maps can be viewed from different perspectives and offer insight into the dynamical aspects of the COVID-19 pandemic for the fifty states in the USA. We have overlaid dynamic information on top of a geographical representation in an intuitive way for decision making. We describe how modeling and simulation of data increase situational awareness, especially when coupled with immersive virtual reality interaction. This paper presents an immersive virtual reality (VR) environment and mobile environment for data visualization using Oculus Rift head-mounted display and smartphones. This work combines neural network predictions with human-centric situational awareness and data analytics to provide accurate, timely, and scientific strategies in combatting and mitigating the spread of the coronavirus pandemic. Testing and evaluation of the data visualization tool have been done with real-time feed of COVID pandemic data set for immersive environment, non-immersive environment, and mobile environment. 

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3. Interactive Visualizations for Crime Data Analysis by Mixed Reality

   Sharma, S; Dronavalli, S; Chellatore, M; Pesaladinne, R (June 2024, Virtual, Augmented and Mixed Reality. HCII 2024. Lecture Notes in Computer Science)

   Chen, JYC; Fragomeni, G eds (Ed.)

   Crime data visualization plays a key role in understanding and dealing with criminal activities. This paper focuses on the integration of mixed reality (MR) and crime data analysis. There are many barriers and challenges when developing MR three-dimensional (3D) environments for visualization and inspection. The main problem is the lack of commonly shared data structures and interfaces between them. The rise in crime rates over the past few years is a huge source of issue for police departments and law enforcement organizations. As the crime rates significantly changed throughout time, both upward and downward, these changes are then compared to external factors, such as population, unemployment, and poverty. There is a need for visualizing the multiple crime datasets in multiple states with external factors. This work proposes a novel interactive approach for loading crime datasets into the HoloLens 2 device and displaying them in a mixed-reality setting for data analysis. By allowing people to engage and analyze datasets in a 3D space, the suggested system seeks to close the gap between data analysis and machine learning. Users can import many datasets, such as spatial, category, and numerical data, into the HoloLens 2 device and interactively visualize crime data for different states simultaneously. The system offers user-friendly capabilities for interactive data visualization in mixed reality once the data has been imported. The dataset is manipulated and transformed by users, who can also rotate, scale, and position it in 3D. To depict various characteristics and dimensions of the data, the system also supports a variety of visual encoding techniques, such as color mapping, size scaling, and spatial layout with the use of the imported datasets and the HoloLens 2’s visualization capabilities, users can discover new insights and intricate linkages within the data. Natural movements and voice instructions allow users to engage with the visible data, enabling a hands-free and immersive data exploration experience. This paper also visualizes the crime data for four different cities: Chicago, Baltimore, Dallas, and Denton. Analyzing crime against factors such as population, employment, unemployment rate, and poverty rates provides information about the complex relationship between social factors and criminal behavior. The results and outcomes of this work will help the police department and law enforcement organizations better understand crime issues and supply insight into factors affecting crime that will help them deploy resources and help their decision-making process. 

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4. A Systematic Review of Virtual Reality Interfaces for Controlling and Interacting with Robots

   https://doi.org/10.3390/app10249051  

   Wonsick, Murphy; Padir, Taskin (December 2020, Applied Sciences)

   null (Ed.)

   There is a significant amount of synergy between virtual reality (VR) and the field of robotics. However, it has only been in approximately the past five years that commercial immersive VR devices have been available to developers. This new availability has led to a rapid increase in research using VR devices in the field of robotics, especially in the development of VR interfaces for operating robots. In this paper, we present a systematic review on VR interfaces for robot operation that utilize commercially available immersive VR devices. A total of 41 papers published between 2016–2020 were collected for review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Papers are discussed and categorized into five categories: (1) Visualization, which focuses on displaying data or information to operators; (2) Robot Control and Planning, which focuses on connecting human input or movement to robot movement; (3) Interaction, which focuses on the development of new interaction techniques and/or identifying best interaction practices; (4) Usability, which focuses on user experiences of VR interfaces; and (5) Infrastructure, which focuses on system architectures or software to support connecting VR and robots for interface development. Additionally, we provide future directions to continue development in VR interfaces for operating robots. 

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5. Real-Time Data Analytics of COVID Pandemic Using Virtual Reality

   https://doi.org/10.1007/978-3-030-77599-5_9  

   Sharma, S; Bodempudi, S.T; Reehl, A (July 2021, Lecture notes in computer science)

   Chen, J.Y.C.; Fragomeni, G (Ed.)

   Visualizing data effectively is critical for the discovery process in the age of big data. We are exploring the use of immersive virtual reality platforms for scientific data visualization for COVID-19 pandemic. We are interested in finding ways to better understand, perceive and interact with multidimensional data in the field of cognition technology and human-computer interaction. Immersive visualization leads to a better understanding and perception of relationships in the data. This paper presents a data visualization tool for immersive data visualizations based on the Unity development platform. The data visualization tool is capable of visualizing the real-time COVID pandemic data for the fifty states in the USA. Immersion provides a better understanding of the data than traditional desktop visualization tools and leads to more human-centric situational awareness insights. This research effort aims to identify how graphical objects like charts and bar graphs depicted in Virtual Reality tools, developed in accordance with an analyst’s mental model can enhance an analyst’s situation awareness. Our results also suggest that users feel more satisfied when using immersive virtual reality data visualization tools and thus demonstrate the potential of immersive data analytics. 

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